Towards a Carbon Data Science
This report provides a critical review of the emissions accounting, reporting and footprinting of carbon dioxide (CO2) currently practiced in the industry to develop a data science for carbon. While providers of carbon footprinting deserve considerable credit for educating asset managers and effectively building an industry, the quality of corporate carbon accounting and reporting still poses significant challenges. Statistical concepts related to carbon footprinting also need further development. We conclude our report by highlighting the three main challenges to be in arriving at Carbon Data Science. First, the vast majority of corporations need to be incentivised to report their carbon emissions accurately, coherently and consistently across reporting schemes. Second, while it seems inevitable for corporations to use estimations in producing their carbon emission inventory, these estimations should be made in compliance with the precautionary principle (i.e. if in doubt, err on the side of the planet). The precautionary principle should equivalently be applied to estimations of carbon emissions by those corporations not (yet) reporting themselves. Third, from an investor perspective concerned about aggregating corporate carbon footprints, the issue of ‘double counting’ has to be addressed more succinctly. For instance a utility provider’s scope 1 is the scope 2 of many other firms and, consequently, some investors’ portfolio carbon footprint might be overstated. While we limit our report to CO2 for simplicity, we consider our findings equivalently applicable to the other greenhouse gases.
|Published on||17th March 2016|
|Authors||Pei-Shan Yu, Hampus Adamsson|